Modulation of Early Human Preadipocyte Differentiation by Glucocorticoids
Bibliographic record
Abstract
Glucocorticoids provide an adipogenic stimulus that is most obvious in the truncal obesity of patients with Cushing's syndrome. Glucocorticoid treatment also strongly potentiates the differentiation of human preadipocytes in culture. However, the molecular basis of these stimulatory effects remains to be defined. In this study, we provide a detailed analysis of the specific contribution of glucocorticoid treatment to the differentiation of primary human preadipocytes cultured in chemically defined medium. Contrary to previous descriptions of glucocorticoids being required throughout the course of differentiation, our results show that glucocorticoid treatment is stimulatory only during the first 48 h of differentiation. Furthermore, stimulation by glucocorticoids and the peroxisome proliferator activator receptor-gamma agonist troglitazone is mediated sequentially. Several details of the early events in the differentiation of human preadipocytes and the contribution of steroid to these events differ from the responses observed previously in murine preadipocyte models. First, glucocorticoid treatment stimulated the early accumulation of CCAAT enhancer binding protein-beta (C/EBPbeta) in primary human preadipocytes. Second, induction of C/EBPalpha in primary human preadipocytes was noted within 4 h of adipogenic stimulus, whereas C/EBPalpha induction is not detected until 24-48 h in the murine 3T3 L1 preadipocyte model. Remarkably, by contrast to human primary preadipocytes, which do not undergo postconfluent mitosis, 3T3 L1 murine preadipocytes stimulated to differentiate under chemically defined conditions required glucocorticoids to survive the clonal expansion that precedes terminal differentiation, revealing a novel signal imparted by glucocorticoids in this immortalized murine cell system.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".